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50match
bagsking11.com
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0 co-citations3 shared tech1 shared categoryshopping
48match
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42match
bangdai-select.com
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30match
allambieorchard.com
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0 co-citations3 shared tech0 shared categorygrocery-shopping
30match
aogotrading.com
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0 co-citations3 shared tech0 shared categorychildren-s-games-and-toys
30match
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0 co-citations3 shared tech0 shared categoryhousehold-supplies
28match
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28match
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28match
hkershop.com
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0 co-citations0 shared tech1 shared categoryshopping
28match
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28match
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0 co-citations1 shared tech1 shared categoryshopping
27match
hibearbrick.com
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0 co-citations2 shared tech1 shared categoryshopping
27match
2littlebob.com
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26match
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26match
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0 co-citations1 shared tech1 shared categoryshopping
26match
cozzip.com
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26match
mirbz.com
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26match
caxxhome.com
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0 co-citations2 shared tech1 shared categoryshopping

How the match score works

Each match is a 0–100 similarity score — the higher it is, the more two sites resemble one another. It’s computed automatically from our own crawl data (never from what a site says about itself) by combining several independent signals, so a high score means several of them point the same way:

No single signal decides the result — they’re blended together. Treat the score as a way to rank candidates rather than an absolute percentage; the chips on each result show which signals contributed.